However, emotion recognition in conversations has gained popularity only recently due to the emergence of publicly available conversational datasets collected from social media platforms
and scripted situations such as movies and tv-shows [1]}, [2]}.
The main approach towards conversational emotion recognition is to perform contextual modeling in either textual or multimodal setting with deep-learning based algorithms.
[3]} used recurrent neural networks for multimodal emotion recognition followed by [4]}, where party and global states were used for modeling the emotional dynamics. An external knowledge base was used in [5]} with transformer networks to perform emotion recognition. Some of the other important works include [6]}, [7]}, [8]}, [9]}, [10]}.
